نبذة مختصرة : INTRODUCTION: The one-legged balance test is a common screening tool for fall risk. Yet, there is little empirical evidence assessing its prognostic ability. The study aims were to assess the prognostic accuracy of one-legged balance performance in predicting falls and identify optimal cut-points to classify those at greater risk. METHODS: Data from up to 2,000 participants from a British birth cohort born in 1,946 were used. The times an individual could stand on one leg with their eyes open and closed were recorded (max: 30 s) at ages 53 and 60-64. Number of falls in the past year was self-reported at ages 53, 60-64 and 68; recurrent falls (0-1 vs. 2+) and any fall (0 vs. 1+) were considered binary outcomes. Four longitudinal associations between balance times and subsequent falls were investigated (age 53 → 60-64; age 53 → 68; age 60-64 → 68; age 53 & 60-64 → 68). For each temporal association, areas under the curve (AUC) were calculated and compared for a base sex-only model, a sex and balance model, a sex and fall history model and a combined model of sex, balance and fall history. The Liu method was used to identify optimal cut-points and sensitivity, specificity, and AUC at corresponding cut-points. RESULTS: Median eyes open balance time was 30 s at ages 53 and 60-64; median eyes closed balance times were 5 s and 3 s, respectively. The predictive ability of balance tests in predicting either fall outcome was poor (AUC range for sex and balance models: 0.577-0.600). Prognostic accuracy consistently improved by adding fall history to the model (range: 0.604-0.634). Optimal cut-points ranged from 27 s to 29 s for eyes open and 3 s to 5 s for eyes closed; AUC consistently indicated that using "optimal" cut-points to dichotomise balance time provided no discriminatory ability (AUC range:0.42-0.47), poor sensitivity (0.38-0.61) and poor specificity (0.23-0.56). DISCUSSION: Despite previous observational evidence showing associations between better one-legged balance performance and reduced fall risk, the ...
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